This document provides a summary and comparison of relational and non-relational databases. It begins with an introduction describing the purpose and organization. The main sections describe the key aspects of relational databases, including their structure, tools like MySQL and Oracle, and shortcomings. Non-relational databases are then described, including different types (document stores, key-value stores, etc.), advantages over relational databases, and their own shortcomings. Comparisons are drawn between relational and non-relational databases and their common tools.

1. A Survey and Comparison of Relational and Non-Relational Database
Nishtha Jatana1
Sahil Puri2
Mehak Ahuja3
Ishita Kathuria4
Dishant Gosain5
1
Assistant professor, Department of Computer Science and Engineering, Maharaja Surajmal Institute of Technology, New Delhi, India
2,3,4,5
Student, Department of Computer Science and Engineering, Maharaja Surajmal Institute of Technology, New Delhi, India
Abstract
We report the comparison between the two leading type of
Database storage components prevailing in the industry.
The Database is largely concerned with managing massive
amount of data in a consistent, stable, repeatable and quick
manner. The prominent features of both relational as well
as non relational databases have been specified which form
the basis of the comparison between the two types of
database. The relational model is based on mathematical
theory(set theory, relational theory) whereas the non-
relational databases may or may not have a single
groundwork mathematical theory. Relational model is
beneficial when it comes to reliability, flexibility,
robustness, scalability requirements but in order to cater to
the needs of modern applications where the data is huge
and generally unstructured; Non-relational databases show
true signs of usability here. Based on the characteristics,
commonly used tools of relational and non relational
databases are mentioned along with brief introduction of
the tools. Comparison has been done between the tools to
notify the distinctive features of tools of relational and non
relational database. Conclusive remarks about the two
categories of database have been mentioned.
1. INTRODUCTION
Our research comprises of studying various relational and
non-relational databases for storing and retrieval of large
amount of data. The attributes and features of both are
listed in the following columns.
Database is a collection of large volumes of data. Database
Management System is an organized way of managing,
retrieving and storing the data. The few actions that can be
performed on database over any other storing mechanism
are as follows:
 Perform complex calculations
 Retrieve records on the basis of matching or
comparing functions
 Update bulk records at an instance.
 Information within multiple tables can be co-
related.
The reliability of database model is checked with the help
of ACID properties.
 Atomicity stands for ‘everything or nothing’. If any
part of the transaction is left incomplete then the
entire transaction is considered failed.
 Consistency ensures that a database before and after
any transaction is stable at a valid state.
 Isolation ensures that multiple transactions
executing at the same time do not affect one
another's execution. Thus, requiring the
concurrent transactions to be serialized.
 Durability ensures that once a transaction has been
committed it will remain in the same state i.e.
stored permanently even if there are some errors,
or even if the system crash or power loss occurs.
When the set of data items are organized with the help of
formally described tables the database formed is known as
relational database. It can easily be accessed, created and
extended. Because of this reason it is a predominant choice
of storing data over hierarchical model or network model.
On the other hand, when traditional tables are not used to
store data, it is known as non- relational database. These
databases may store the data in the form of key- value
stores, XML format, multidimensional databases and so
on.
Non- relational databases, also commonly known as
NOSQL(Not Only SQL), provide elastic scaling meaning
that they scale up transparently by adding a new node, and
they are usually designed with low-cost hardware in
mind. The other advantages that come packaged with non
relational databases are: schema-free, easy replication
support, simple API, eventually consistent / BASE (not
ACID), a huge amount of data and more.
This paper is organized as follows.Section2 consists of a
general overview of relational database system. Section 3
elaborates on a non-relational databases .Finally the results
of the survey and comparison are discussed in section 4.
International Journal of Engineering Research & Technology (IJERT)
Vol. 1 Issue 6, August - 2012
ISSN: 2278-0181
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2. 2. RELATIONAL DATABASE
2.1 Overview of Relational Database Model
E.F Codd invented the relational database in 1970. A
database is an application that allows storing and retrieving
data very rapidly. A relational database is a collection of
data items organized in formally-described tables from
which data can be accessed or reassembled in many
different ways. Relational Database is a set of tables
referred to as relation with data category described in
columns similar to spreadsheets. Each row contains a
unique instance of data for the corresponding data
category. While creating a relational database domain of
possible values along with constrains are applied to the
data. It is the relation between the tables that makes it a
‘relation’ table. They require few assumptions about how
data will be extracted from the database. As a result, the
same database can be viewed in many different ways.
Mostly all the relational databases use Structured Query
Language (SQL) to access and modify the data stored in
the database. Originally it was based upon relational
calculus and relational algebra and is subdivided into
elements such as clauses, predicates, queries and
statements.
Some of the benefits of the database designed according to
the relational model are:
 Most of the information is stored in the database
and not in the application, so the database is self
documenting.
 It is easy to add, update or delete data.
 It gives benefits of data summarization, retrieval
and reporting.
 The database is structured in a tabular form with
highly related tables; the nature of the database is
predictable.
 Also, any changes required to make in the schema
of the database is quite simple.
2.2. Tools of Relational Database
The two most extensively used relational databases are
MySQL and Oracle. MySQL is more popular with the
websites. It is a light weight system which is extremely fast
but Oracle is majorly used in case of large database
requirement like Banking, Insurance, ERP and finance
companies. It is used to solve complex problems and
supports large OLTP environments.
Though they majorly work in a similar fashion yet there
are a few differences between them.
 Oracle is a high cost system that can be afforded
only by large organizations unlike MySQL which
is open source database. But MySQL lacks on add
on facilities and robustness supported by Oracle.
 Oracle has large tablespace, role management,
snapshots, packages and synonyms unlike
MySQL.
 The syntax of Oracle is high flexible. It provides
integrated programming language like PL/SQL. It
also has broader command structure as compared
to MySQL.
 The security of Oracle is very tight and bounded.
MySQL provides three security parameters like
username, password and location whereas Oracle
provides advance security enhancements by
creating profiles, local authentication and external
authentication.
 Oracle is case insensitive but MySQL is case
sensitive when it comes to database and table
names.
 For data transfer Oracle uses XML but this
language is not supported by MySQL.
 MySQL has CHAR and VARCHAR for character
types on the contrary Oracle has four character
types namely CHAR, NCHAR, VARCHAR2, and
NVARCHAR2 all types need to be minimum of 1
byte long.
 Oracle is a highly extensive database system that
supports advanced functionality like Active Data
Guard, Audit Vault, Partitioning and Data Mining.
MySQL does not support Audit Vault on the
server.
 Temporary tables are handled differently by Oracle
and MySQL. In MySQL the tables are dropped
automatically after the current session ends and
are visible only to the current user session but in
case of Oracle the tables have to be explicitly
dropped. The tables are visisble to all the sessions
but the data inside is visible only to the current
user session.
 MySQL has backup utilities like mysqldump and
mysqlhotcopy. Oracle has Recovery Manager
(RMAN) whaich is the most important backup
utility. Using this backup scheduling can be
automated using a very few commands and
scripts.
Oracle has tons of features starting from user defined
data types to database management tools extending
upto XML. Because of its high functionality it has
reduced the need of any third party software or tool. It
supports large business application.
MySQL is used in case of high speed web and gaming.
It supports small sized data warehouse and OLTP
systems so it can be used in small projects in smaller
companies at low cost. However it requires third party
softwares and lacks the robust functionality provided
by Oracle.
International Journal of Engineering Research & Technology (IJERT)
Vol. 1 Issue 6, August - 2012
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3. 2.2. Shortcomings of Relational Database
Relational Databases though conventionally accepted
suffer from a number of drawbacks which are discussed
in this section
1.) Relational databases do not support high
scalability, until a certain point better hardware can
be employed but beyond that point the database
must be distributed.
2.) One of the major disadvantage is data is stored in
relational database in form of tables, this structure
can give rise to high complexity in case data
cannot be easily encapsulated in a table.
3.) Much of the features provided by relational
databases are not used hence simply add to the cost
as well as the complexity of the database.
4.) Relational Databases make use of SQL, which is
featured to work on structured data, but SQL can
be highly complex when working with
unstructured data.
5.) When the amount of data turns huge the database
has to be partitioned across multiple servers, this
partitioning poses several problems because
joining tables in distributed servers is not an easy
task.
Thus, there was a demanding need to store and access
huge data in a better way, thus giving rise to a newer
form of data storage known as NON-RELATIONAL
DATABASES.
3. NON-RELATIONAL DATABASES
3.1 Overview
Non relational database is a class of systems which manage
databases and it broadly differs from the relational systems
in many significant ways; most important being that it
doesn’t use relations (tables) as its storage structure. Other
factors which differentiate it are it doesn’t use SQL as its
query language, join operations cannot be performed, it
doesn’t guarantee ACID properties and can be scaled
horizontally. There can be many classification for NOSQL
databases that are available today. One of the classification
can based on CAP theorem as is discussed in [1]. Non
relational databases may primarily be classified on the
basis of way of organizing data as follows:
1. Key Value Stores
It allows the app-developer to store schema-less data. This
data consists of a key which is represented by a string and
the actual data which is the value in key-value pair. The
data can be any primitive of programming language, which
may be a string, an integer or an array or it can be an
object. Thus it loosens the requirement of formatted data
for storage, eliminating the need for fixed data model.
2. Document Store
Document Store, also commonly known as “Document
Oriented Database”, is basically a computer program used
for storing, retrieving, updating data stored in database.
The underlying storage structure used in such databases is
a ‘document’. Each Document Store differs in its
implementation of data; however each of it assumes that
data is enclosed and encoded in some standard format
which may be XML, BSON, PDF or Microsoft office.
Each document is represented by a unique key which is a
string (URI or path). An API or a query language is
provided for fast retrieval of documents on the basis of its
content .For e.g. a query that retrieves all the documents in
which certain field is set to some particular value.
3. Graph Database
Graph databases are schema-less databases which use
graph data structures along with nodes, edges and certain
properties to represent data. Nodes may represent entities
like people, business or any other item similar to what
objects represent in any programming language. Properties
designate any pertinent information related to nodes. On
the other hand; edges relate a node to other node or a node
to some property. One can obtain some meaningful pattern
or behavior after studying the interconnection between all
three viz. nodes, properties and edges.
4. Column Oriented Databases
Column Store Databases, unlike Row Databases, store
their data in the form of columns. It serializes all the values
of one column together and so on. Column-oriented
databases are comparatively efficient than row oriented
one’s when new values for a column are entered for all
rows at once as column data can be written efficiently and
replace old data without altering any other columns for the
rows.
5. Object Oriented Databases
Object Oriented Databases also commonly known as
OODBMS), is a database system. It stores its data in the
form of objects. This feature supports inheritance and
hence reusability similar as in object oriented
programming.
6. Grid and Cloud Databases
Grid and Cloud Databases make use of grid and cloud
computing collectively. Grid computing is exploited to
manage heterogeneous and geographically distributed
databases while Cloud Computing provides easy access to
remote hardware and storage resources.
7. XML Databases
XML database is a database management system that is
used to store XML data. In all native XML databases,
XML document is the fundamental storage format.
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4. However in some XML enabled databases, data of the
XML document is divided into parts and these parts are
stored within tables using another XML mapping layer.
Some hybrid XML databases also exist which are
combination of native and XED’s.
8. Multidimensional Databases
Multidimensional Databases store the data as n-
dimensional matrix. All the useful aggregates are also
precompiled and stored, allowing roll-ups and drill-downs
to be answered interactively. Many products use this
approach, like, Arbor Essbase [Arb] and IRI Express [IRI].
Multidimensional databases may use a relational database
as backend in which multidimensional queries are mapped
onto equivalent relational queries. Products which use this
concept are Redbrick and Microstrategy
9. Multivalue Databases
Multivalue database earlier known as PICK database is
such a database which understands three dimension data
directly i.e. fields, values and subvalues. In this, value is a
breakdown of field and subvalue is further breakdown of
value. The tables in this database are extremely flexible
such that if any of the changes are made in the database,
there is no need to shut down the database or rebuild the
database. Also multivalue databases have calculated
columns as they can contain small programs for
calculations.
10. Multimodel Databases
Multimodel databases are a blend of various other non-
relational databases that provides a mix of advantages
offered by various other types mentioned above.
Non-relational databases provide a solution to the
increasing amount of data storage required in the internet
today. With the advent of NOSQL, cloud computing can
now effectively manage the huge amount of data and its
efficient handling. A new architecture known as
CDSA(Cloud data storage architecture) [2] further
improves query performance. In [5] the author shows
performance improvement by using NOSQL instead of
MSQL in execution of a textbook management system.
Non Relational database can be classified in a way as as
shown in Table 1.1. As shown in the table document store,
key value and corresponding XML databases are listed. A
more elaborate description can be found in [6]. A
comparative analysis of various NOSQL databases has
already been done previously in [3] and [10].
Core NoSQL
Systems
Document
Store
Key Value /
Tuple Store
XML
Databases
Hadoop/
HBase
MongoDB DynamoDB Mark Logic
Server
Cassandra CouchDB Azure Table
Storage
EMC
document
xDB
Hypertable RavenDB MEMBASE EXist
Amazon
Simple DB
Citrusleaf Riak Sedna
Cloudata Clusterpoint
Server
Redis BaseX
Cloudera ThruDB LevelIDB Qizx
SciDB Terrastore Chordless Berkely DB
XML
Stratosphere SisoDB GenieDB
SDB Scalaris
Tokyo
Cabinet/Tyrant
GTM
Scalien
Berkeley DB
Voldemort
Dynomite
Table 1.1
3.2. Disadvantages of NOSQL
Apart from various advantages such as high
throughput, horizontal scalability, avoidance of
expensive object relational mapping, Non-Relational
Databases have some shortcomings discussed in [4] and
[7].The most significant ones are discussed here.
1.) Most of the Non-Relational databases are open
source software and though well appreciated, it
compromises in reliability as nobody is responsible
in times of failures.
2.) Many of the Non-Relational databases are disk-
based which implement buffer pool and
multithreading hence require buffer management
and locking features which add on to performance
overhead.
3.) Many Non-relational databases provide BASE
properties and sacrifice conventional ACID
properties as a step to increase performance. This
could mean than non-relational databases
compromise on consistency within the database.
4.) Because of flouting ACID properties, the degree of
reliability provided by non-relational databases is
lower than what is provided by the relational
databases. Developers have to rope in
programming to apply ACID restraints which
could have been provided easily in relational
databases.
5.) As the market is still unfamiliar to non-relational
databases, it causes a major reason for developers
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5. to use it and in determining whether it will be
beneficial or not.
NoSQL solutions have emerged and risen because of
deficiencies in existing RDBMS technology.
 Data which is updated or written more often rather
than being read should consider using a key-value
store like Redis, or a document store like MongoDB.
 Data which is big must try considering distributed
database system like Hadoop.
 Files which store data in binary form (such as audio
files etc) work greatly with a database that aids to user’s
browser, like Amazon S3.
 Transient data must be worked out with a transient
datastore like Memcache.0
 Data which needs to be replicated to number of
locations (eg. A database between a web application
and a device like mobile) should use CouchDB.
 Applications which require high availability i.e. where
minimizing downtime is crucial, must utilize the
features of datastores like Casandra and Riak which
provide automatic clustering and redundant setup.
 Data which needs to work with Graphs must use
Neo4J - built for traversing social graphs
4. Results and Discussions
Finally , we can conclude and highlight the major
differences between the two types of databases as follows :
S.NO NON- RELATIONAL RELATIONAL
1. High data throughput Low data throughput
2. Highly scalable Less Scalable
3. The data can be inserted anytime
without defining a schema. The
data can be altered anytime with
any major issue. So its highly
flexible
In this case the data has to
fit in predefined tables or
structure.
4. Performance can be enhanced by
caching data into system memory.
Caching has to be done
with the help of special
infrastructure.
5. In the application multiple
operation transactions can be
implemented.
Transactional
6. Single index, key value store Index available on
multiple column.
7. Provide BASE properties Provides ACID properties
8. Non relational databases
compromise on Consistency
Provide better consistency
than Non-relational
databases
9. Data duplication is allowed which
threatens data integrity. Moreover
updating one record means
updating all other duplicate
records which means high
overhead.
The relational database
design process eliminates
record duplication,
preventing inconsistent
data from occupying the
database
10. Searching in Non-relational
database is inefficient especially
those based on multiple criteria,
as they require more than one
pass.
Relational database
organization allows a
query language such as
SQL to use the primary
key shared between tables
to quickly and efficiently
collate and return the
requested records
Table 1.2
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